Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1038/s41558-018-0359-7 |
Towards operational predictions of the near-term climate | |
Kushnir, Yochanan1; 39;Kane, Terence2 | |
2019-02-01 | |
发表期刊 | NATURE CLIMATE CHANGE
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ISSN | 1758-678X |
EISSN | 1758-6798 |
出版年 | 2019 |
卷号 | 9期号:2页码:94-101 |
文章类型 | Article |
语种 | 英语 |
国家 | USA; England; Canada; Spain; Japan; Switzerland; Germany; Australia; Peoples R China |
英文摘要 | Near-term climate predictions - which operate on annual to decadal timescales - offer benefits for climate adaptation and resilience, and are thus important for society. Although skilful near-term predictions are now possible, particularly when coupled models are initialized from the current climate state (most importantly from the ocean), several scientific challenges remain, including gaps in understanding and modelling the underlying physical mechanisms. This Perspective discusses how these challenges can be overcome, outlining concrete steps towards the provision of operational near-term climate predictions. Progress in this endeavour will bridge the gap between current seasonal forecasts and century-scale climate change projections, allowing a seamless climate service delivery chain to be established. |
领域 | 资源环境 |
收录类别 | SCI-E ; SSCI |
WOS记录号 | WOS:000456994900011 |
WOS关键词 | MODEL INTERCOMPARISON PROJECT ; SURFACE-TEMPERATURE ; DECADAL PREDICTION ; SUBPOLAR GYRE ; EXPERIMENTAL-DESIGN ; OCEAN REANALYSES ; PACIFIC ; PREDICTABILITY ; VARIABILITY ; CMIP5 |
WOS类目 | Environmental Sciences ; Environmental Studies ; Meteorology & Atmospheric Sciences |
WOS研究方向 | Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/34613 |
专题 | 资源环境科学 |
作者单位 | 1.Columbia Univ, Lamont Doherty Earth Observ, Palisades, NY 10964 USA; 2.Met Off Hadley Ctr Climate Predict & Res, Exeter, Devon, England; 3.Univ Exeter, Coll Engn Math & Phys Sci, Exeter, Devon, England; 4.Iowa State Univ, Dept Agron, Ames, IA USA; 5.European Ctr Medium Range Weather Forecasts, Reading, Berks, England; 6.Environm Canada & Climate Change, Canadian Ctr Climate Modelling & Anal, Victoria, BC, Canada; 7.ICREA, Barcelona, Spain; 8.Barcelona Supercomp Ctr, Barcelona, Spain; 9.Univ Reading, Dept Meteorol, Natl Ctr Atmospher Sci, Reading, Berks, England; 10.Univ Tokyo, Atmosphere & Ocean Res Inst, Kashiwa, Chiba, Japan; 11.World Meteorol Org, World Climate Applicat & Serv Div, Climate Predict & Adaptat Branch, Climate & Water Dept, Geneva, Switzerland; 12.Climate Predict Ctr, College Pk, MD USA; 13.Max Planck Inst Meteorol, Hamburg, Germany; 14.GEOMAR Helmholtz Ctr Ocean Res Kiel, Kiel, Germany; 15.Christian Albrechts Univ Kiel, Kiel, Germany; 16.Deutsch Wetterdienst, Hamburg, Germany; 17.CSIRO Oceans & Atmosphere, Hobart, Tas, Australia; 18.Univ Colorado, Cooperat Inst Res Environm Sci, Boulder, CO USA; 19.NOAA, Phys Sci Div, Earth Syst Res Lab, Boulder, CO USA; 20.Bur Meteorol, Melbourne, Vic, Australia; 21.Univ Calif Los Angeles, Los Angeles, CA USA; 22.Japan Meteorol Agcy, Tokyo, Japan; 23.WCRP WMO, Geneva, Switzerland; 24.Chinese Acad Sci, Inst Atmospher Phys, LASG, Beijing, Peoples R China |
推荐引用方式 GB/T 7714 | Kushnir, Yochanan,39;Kane, Terence. Towards operational predictions of the near-term climate[J]. NATURE CLIMATE CHANGE,2019,9(2):94-101. |
APA | Kushnir, Yochanan,&39;Kane, Terence.(2019).Towards operational predictions of the near-term climate.NATURE CLIMATE CHANGE,9(2),94-101. |
MLA | Kushnir, Yochanan,et al."Towards operational predictions of the near-term climate".NATURE CLIMATE CHANGE 9.2(2019):94-101. |
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